Neural Proximal Gradient Descent for Compressive Imaging

1 June 2018

Morteza Mardani

Qingyun Sun

Shreyas S. Vasawanala

Papers citing "Neural Proximal Gradient Descent for Compressive Imaging"

30 / 30 papers shown

Title
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems Eric Chen Xi Chen A. Maleki S. Jalali 38 0 0 08 Jan 2025
Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures Michael Unser Alexis Goujon Stanislas Ducotterd 31 2 0 23 Aug 2024
Learning Regularization for Graph Inverse Problems Moshe Eliasof Md Shahriar Rahim Siddiqui Carola-Bibiane Schönlieb Eldad Haber GNN 42 0 0 19 Aug 2024
Graph Neural Reaction Diffusion Models Moshe Eliasof Eldad Haber Eran Treister DiffM AI4CE 38 2 0 16 Jun 2024
A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning Wanyu Bian 40 5 0 03 Jun 2024
A General Continuous-Time Formulation of Stochastic ADMM and Its Variants Chris Junchi Li 37 0 0 22 Apr 2024
What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang Sam Buchanan Jeremias Sulam 31 11 0 22 Oct 2023
$Learning Trees of $\ell_0$-Minimization Problems$ Learning Trees of $\ell_0$ -Minimization Problems G. Welper 21 0 0 06 Feb 2023
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 33 2 0 19 Aug 2022
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 26 12 0 02 Jul 2022
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction Beliz Gunel Arda Sahiner Arjun D Desai Akshay S. Chaudhari S. Vasanawala Mert Pilanci John M. Pauly MedIm 22 7 0 21 Apr 2022
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging Kerstin Hammernik Thomas Kustner Burhaneddin Yaman Zhengnan Huang Daniel Rueckert Florian Knoll Mehmet Akçakaya PINN MedIm AI4CE 32 70 0 23 Mar 2022
Learning A 3D-CNN and Transformer Prior for Hyperspectral Image Super-Resolution Qing Ma Junjun Jiang Xianming Liu Jiayi Ma ViT 34 53 0 27 Nov 2021
Equivariant Imaging: Learning Beyond the Range Space Dongdong Chen Julián Tachella Mike E. Davies SSL 34 95 0 26 Mar 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 54 225 0 23 Mar 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 49 181 0 16 Feb 2021
Phase Retrieval using Expectation Consistent Signal Recovery Algorithm based on Hypernetwork Chang-Jen Wang Chao-Kai Wen Shang-Ho S. Tsai Shi Jin Geoffrey Ye Li 27 5 0 12 Jan 2021
Model Adaptation for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett OOD MedIm 16 48 0 30 Nov 2020
Unsupervised MRI Reconstruction with Generative Adversarial Networks Elizabeth K. Cole John M. Pauly S. Vasanawala Frank Ong GAN MedIm 22 50 0 29 Aug 2020
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data Alan Q. Wang Adrian Dalca M. Sabuncu 31 26 0 29 Jul 2020
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport Gilles Puy Alexandre Boulch Renaud Marlet 3DPC OT 137 183 0 22 Jul 2020
Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations Dongdong Chen Mike E. Davies Mohammad Golbabaee 19 16 0 27 Jun 2020
Deep Learning Techniques for Inverse Problems in Imaging Greg Ongie A. Jalal Christopher A. Metzler Richard G. Baraniuk A. Dimakis Rebecca Willett 13 521 0 12 May 2020
Solving Inverse Problems with a Flow-based Noise Model Jay Whang Qi Lei A. Dimakis 64 36 0 18 Mar 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 35 290 0 13 Jan 2020
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 45 639 0 28 Oct 2019
Momentum-Net: Fast and convergent iterative neural network for inverse problems Il Yong Chun Zhengyu Huang Hongki Lim Jeffrey A. Fessler 19 81 0 26 Jul 2019
Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning Joseph Y. Cheng Feiyu Chen Christopher M. Sandino Morteza Mardani John M. Pauly S. Vasanawala 21 12 0 19 Mar 2019
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling Shanshan Wu A. Dimakis Sujay Sanghavi Felix X. Yu D. Holtmann-Rice Dmitry Storcheus Afshin Rostamizadeh Sanjiv Kumar SSL 23 53 0 26 Jun 2018
Compressed Sensing with Deep Image Prior and Learned Regularization Dave Van Veen A. Jalal Mahdi Soltanolkotabi Eric Price S. Vishwanath A. Dimakis 33 178 0 17 Jun 2018